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There are many possible strategies to promote naturalization in anthropogenic landscapes to mitigate global change effects. We combined large-scale databases available for continental Spain on: (1) distribution of breeding birds, (2) forest inventory stands, (3) land-use cover, (4) 18 global climate models recently developed at local scales, and (5) historical and genetically-based information on the distribution of natural versus planted pine forests, to analyze whether back to nature strategies may help to mitigate biodiversity loss due to climate change. We performed the analysis along environmental and ecological gradients of pine forests in Southern Europe. Models suggested that, naturalization strategies, in this case defined by the replacement of planted pine forests and eucalyptus forests by natural pine forests, could help to mitigate the expected loss of bird diversity due to climate change, but that mitigation efficiency will vary along environmental and ecological gradients. Maximum levels of diversity mitigation were predicted at intermediate levels of naturalization, with lower bird richness in areas where all pine forests were either planted or naturalized. Efficiency also varied spatially, given that both cold- and hot-spots of climate-driven bird diversity loss were identified. Transforming planted forest into natural forest is not a mitigation panacea, and additional regionally-adapted strategies may be identified to mitigate the expected biodiversity loss in forest ecosystems., Competing Interests: The authors have declared that no competing interests exist.

Climate change is gravely affecting forest ecosystems, resulting in large distribution shifts as well as in increasing infection diseases and biological invasions. Accordingly, forest management requires an evaluation of exposure to climate change that should integrate both its abiotic and biotic components. Here we address the implications of climate change in an emerging disease by analysing both the host species (Pinus pinaster, Maritime pine) and the pathogen's (Fusarium circinatum, pitch canker) environmental suitability i.e. estimating the host's risk of habitat loss and the disease`s future environmental range. We constrained our study area to the Spanish Iberian Peninsula, where accurate climate and pitch canker occurrence databases were available. While P. pinaster is widely distributed across the study area, the disease has only been detected in its north-central and north-western edges. We fitted species distribution models for the current distribution of the conifer and the disease. Then, these models were projected into nine Global Climate Models and two different climatic scenarios which totalled to 18 different future climate predictions representative of 2050. Based on the level of agreement among them, we created future suitability maps for the pine and for the disease independently, which were then used to assess exposure of current populations of P. pinaster to abiotic and biotic effects of climate change. Almost the entire distribution of P. pinaster in the Spanish Iberian Peninsula will be subjected to abiotic exposure likely to be driven by the predicted increase in drought events in the future. Furthermore, we detected a reduction in exposure to pitch canker that will be concentrated along the north-western edge of the study area. Setting up breeding programs is recommended in highly exposed and productive populations, while silvicultural methods and monitoring should be applied in those less productive, but still exposed, populations., Competing Interests: The authors have declared that no competing interests exist.

Understanding the complex process of climate change implies the knowledge of all possible determinants of CO emissions. This paper studies the influence of several institutional determinants on CO emissions, clarifying which variables are relevant to explain this influence. For this aim, Genetic Programming and Artificial Neural Networks are used to find an optimal functional relationship between the CO emissions and a set of historical, economic, geographical, religious, and social variables, which are considered as a good approximation to the institutional quality of a country. Besides this, the paper compares the results using these computational methods with that employing a more traditional parametric perspective: ordinary least squares regression (OLS). Following the empirical results of the cross-country application, this paper generates new evidence on the binomial institutions and CO emissions. Specifically, all methods conclude a significant influence of ethnolinguistic fractionalization (ETHF) on CO emissions. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]